臺灣博碩士論文加值系統

本文以Component GARCH模型探討臺灣股票市場上市指數報酬波動與交易量的關係，為了討論資訊代理變數的效果將交易量區分為總交易量變動率、預期交易量變動率與未預期交易量變動率，分別探討指數報酬長期（永久性）波動和短期（暫時性）波動與交易量的關係，並以Fama and French（2013）五因子模型（CAPM beta值、市值比、股價淨值比、股價營收比、週轉率）分析最高群組及最低群組的波動影響，本研究主要發現如下：

1、加權指數、電子類、金融保險類的永久性衝擊對長期波動的影響為正向顯著且大於暫時性衝擊對短期波動的負向影響，實施QE2的衝擊影響大於QE1。

2、加權指數、電子類的總交易量變動率對短期波動為正向顯著影響且大於總交易量變動率對長期波動的正向顯著影響，金融保險類的總交易量變動率對長期波動為正向影響且大於總交易量變動率對短期波動的正向影響。

3、加權指數、電子類、市值比重最高群組的預期交易量變動率對長期波動和未預期交易量對短期波動為正向關係，預期交易量對短期波動為負向關係，預期交易量變動率對長期和短期波動的影響大於未預期交易量變動率對長期和短期波動的影響，實施QE2的衝擊影響大於QE1。

4、CGARCH模型加入資訊代理變數，未使得永久性波動的持續性有大幅降低的現象，因此臺灣股票市場較符合SIAH假說。

5、研究期間為全期時，市值比重最低群組、股價營收比最高群組、週轉率最高群組，暫時性衝擊對波動的影響大於永久性衝擊對波動的影響。

This paper uses Component GARCH model to study the stock index return volatility-volume relationships of Taiwan stock market. The trading volume is decomposed into two parts, namely the percentage change of total volume, the percentage change of expected volume and the percentage change of unexpected volume to study the long run (permanent) and short run (transitory) volatility-volume relations. Fama and French (2013) five factors model (CAPM beta, market weighting, P/B, P/EPS, turnover) is used to investigate the impacts of the highest volatility and the lowest volatility groups. The major findings are the following: The long term impacts of TAIEX, Electronics Index, and Finance and Insurance index on the long term volatility are significant and positive. The short term impacts of TAIEX, Electronics Index, and Finance and Insurance index on the short term volatility are significant and negative. The long term positive impacts on the long term volatility are bigger than the short term negative impacts on the short term volatility. The QE2 has greater impact than the QE1. The impacts of TAIEX and Electronics Index trading volume percentage changes on the short term volatility and long term volatility are both significant and positive. The impacts of Finance and Insurance Index trading volume percentage change on the short term volatility and long term volatility are both positive, with greater impact on the long term volatility. The impacts of expected trading volume percentage changes of TAIEX, Electronics Index, and the highest weight of market value group on the long term volatility are positive. The impacts of expected (unexpected) trading volume percentage changes of TAIEX, Electronics Index, and the highest weight of market value group on the short term volatility are negative (positive). The impacts of expected trading volume percentage changes on the short term and long term volatilities are greater than the impacts of the unexpected trading volume percentage changes on the short term and long term volatilities. The impact in QE2 is bigger than the impact in QE1. Including volume in the CGARCH models show that the volatility persistence does not decline deeply. Evidences show that Taiwan stock market satisfies the SIAH. In the whole research period, the transitory component shock is greater than the permanent component shock for the lowest market weight group, the highest price earning ratio group, and the highest turnover rate group.

目錄

中文摘要 i

ABSTRACT ii

誌謝 iv

目錄 v

表目錄 vi

圖目錄 vii

附表目錄 ix

第壹章 緒論 1

第一節 研究背景與動機 1

第二節 研究目的 5

第三節 研究貢獻 6

第四節 文章架構 8

第貳章 文獻回顧 9

第一節 價格和交易量的假說與實證 9

第二節 GARCH模型在價量關係上的研究 12

第三節 Component GARCH模型發展及實證 15

第四節 Component GARCH模型實證小結 19

第參章 研究方法 20

第一節 基本檢定 20

第二節 CGARCH模型設立 36

第三節 CGARCH模型的意涵 41

第四節 建立假說 43

第肆章 實證結果與分析 47

第一節 CGARCH 模型的估計 47

第二節 美國實施第一次量化寬鬆CGARCH 模型的估計 75

第三節 美國實施第二次量化寬鬆CGARCH模型的估計 95

第四節 全期、QE1、QE2的衝擊比率的結果分析 155

第伍章 結論與建議 159

第一節 結論 160

第二節 後續建議 164

參考文獻 165

附錄 174







表目錄

表3-1 指數與交易量的單根檢定 22

表3-2 加權指數與類股指數報酬率、總交易量變動率、未預期交易量變動率敍述統計 24

表3-3 產業別以Fama and French五因子區分的群組統計表 29

表3-4 結構性轉變檢定 34

表4-1 全期CGARCH未加入交易量模型 50

表4-2 全期CGARCH加入總交易量變動率模型 55

表4-3全期CGARCH加入預期交易量變動率和未預期交易量變動率模型 61

表4-4 QE1後期CGARCH未加入交易量模型 78

表4-5 QE1後期CGARCH加入總交易量變動率模型 83

表4-6 QE1後期CGARCH加入預期交易量變動率和未預期交易量變動率模型 89

表4-7 QE2前期CGARCH未加入交易量模型 98

表4-8 QE2前期CGARCH加入總交易量變動率模型 103

表4-9 QE2前期CGARCH加入預期交易量變動率和未預期交易量變動率模型 108

表4-10 QE2後期CGARCH未加入交易量模型 116

表4-11 QE2後期CGARCH加入總交易量變動率模型 121

表4-12 QE2後期CGARCH加入預期交易量變動率和未預期交易量變動率模型 126

表4-13 CGARCH無加量模型以五因子區分最高群組和最低群組彚總表 133

表4-14 CGARCH加入總交易量變動率模型以五因子區分最高群組和最低群組彚總表 140

表4-15 CGARCH加入預期交易量變動率和未預期交易量變動率模型以五因子區分最高群組和最低群組彚總表 146

表4-16 各期間及模型衝擊比率 157























圖目錄

圖4-1 加權指數CGARCH模型條件變異數、長期波動、短期波動趨勢分解圖 67

圖4-2 水泥類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 67

圖4-3 食品類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 68

圖4-4 塑膠類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 68

圖4-5 紡織纖維類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 68

圖4-6 電機機械類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 68

圖4-7 電器電纜類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 69

圖4-8 化學生技醫療類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 69

圖4-9 化學類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 69

圖4-10 生技醫療類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 69

圖4-11 玻璃陶瓷類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 70

圖4-12 造紙類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 70

圖4-13 鋼鐵類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 70

圖4-14 橡膠類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 70

圖4-15 汽車類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 71

圖4-16 電子類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 71

圖4-17 半導體類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 71

圖4-18 電腦及週邊設備類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 71

圖4-19 光電類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 72

圖4-20 通信網路類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 72

圖4-21 電子零組件類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 72

圖4-22 電子通路類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 72

圖4-23 資訊服務類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 73

圖4-24 其他電子業類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 73

圖4-25 營造建材類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 73

圖4-26 航運類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 73

圖4-27 觀光類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 74

圖4-28 金融保險類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 74

圖4-29 百貨貿易類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 74

圖4-30 油電燃氣類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 74

圖4-31 其他類CGARCH 模型條件變異數、長期波動、短期波動趨勢分解圖 75

















































附表目錄

附表1 QE1前期CGARCH未加入交易量模型 174

附表2 QE1前期CGARCH加入總交易量變動率模型 177

附表3 QE1前期CGARCH加入預期交易量變動率和未預期交易量變動率模型 180

附表4 QE1中期CGARCH未加入交易量模型 185

附表5 QE1中期CGARCH加入總交易量變動率模型 188

附表6 QE1中期CGARCH加入預期交易量變動率和未預期交易量變動率模型 191

附表7 QE2中期CGARCH未加入交易量模型 195

附表8 QE2中期CGARCH加入總交易量變動率模型 198

附表9 QE2中期CGARCH加入預期交易量變動率和未預期交易量變動率模型 202

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